High-quality alt text is crucial for making scientific figures accessible to blind and low-vision readers. Crafting complete, accurate alt text is challenging even for domain experts, as published figures often depict complex visual information and ...

Human-centered AI aims to bridge the gap between machine decision-making and human understanding. However, even for classification tasks where deep neural networks have achieved superb performance, there are currently few methods that link humans and AI ...

AI systems have been known to amplify biases in real-world data. Explanations may help human-AI teams address these biases for fairer decision-making. Typically, explanations focus on salient input features. If a model is biased against some protected ...

Group decision making plays a crucial role in our complex and interconnected world. The rise of AI technologies has the potential to provide data-driven insights to facilitate group decision making, although it is found that groups do not always utilize ...

Traditionally, sports commentators provide viewers with diverse information, encompassing in-game developments and player performances. Yet young adult football viewers increasingly use mobile devices for deeper insights during football matches. Such ...

While 33.6% of college students suffer from mental health problems, only 24.6% of these students with symptoms would seek professional help due to their personal attitudes or costs associated with therapy. Psychotherapy chatbots may offer a solution as ...

Community organizations face challenges in harnessing the power of qualitative data analysis, or sensemaking, to understand the diverse perspectives and needs brought up by their constituents. One of the most time-consuming and tedious parts of ...

In traffic engineering, cities rely on large detector datasets to manage traffic. Visualizing these big, multi-dimensional datasets poses challenges such as overplotting and dimension reduction, often rendering traditional visualization techniques ...

This research explores integration of a Large Language Model (LLM) fine-tuned to conversationally control the user interface (UI) for a Semantic Automation Layer (SAL). We condense SAL capabilities from prior work and prioritize with business analysts ...

Pattern-recognition-based arm prostheses rely on recognizing muscle activation to trigger movements. The effectiveness of this approach depends not only on the performance of the machine learner but also on the user’s understanding of its recognition ...

While writing peer reviews resembles an important task in science, education, and large organizations, providing fruitful suggestions to peers is not a straightforward task, as different user interaction designs of text suggestion interfaces can have ...

Representations of AI agents in user interfaces and robotics are predominantly White, not only in terms of facial and skin features, but also in the synthetic voices they use. In this paper we explore some unexpected challenges in the representation of ...

As machine learning (ML) gains wider adoption in real-world applications, the validation of ML models becomes fundamental for its productization, particularly in safety-critical applications. Recently, data slice finding has emerged as a popular method ...

Object detection tasks are central to the development of datasets and algorithms in computer vision and machine learning. Despite its centrality, object detection remains tedious and time-consuming due to the inherent interactions that are often ...

Synthesizers are powerful tools that allow musicians to create dynamic and original sounds. Existing commercial interfaces for synthesizers typically require musicians to interact with complex low-level parameters or to manage large libraries of premade ...

The rapid advancement of the automotive industry towards automated and semi-automated vehicles has rendered traditional methods of vehicle interaction, such as touch-based and voice command systems, inadequate for a widening range of non-driving related ...

Large-scale 3D point clouds are often used as training data for 3D semantic segmentation, but the labor-intensive nature of the annotation process challenges the acquisition of sufficient labeled data. Meanwhile, there has been limited research on ...

When individuals are talking while performing multiple tasks at the same time, it is sometimes easy to miss parts of a conversation and misinterpret subsequent statements or have difficulty following the conversation. In this work, we aim to identify ...

Recent years have witnessed a dramatic growing trend of Virtual YouTubers (VTubers) as a new business on social media, such as YouTube, Twitch, and TikTok. However, a significant challenge arises when VTuber voice actors face health issues or retire, ...

Large language model (LLM) prompting is a promising new approach for users to create and customize their own chatbots. However, current methods for steering a chatbot’s outputs, such as prompt engineering and fine-tuning, do not support users in ...